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stat.ME2026
Prior-data fitted networks for variable selection
Omar Melikechi
Prior-data fitted networks (PFNs) have become state-of-the-art for tabular prediction but remain underexplored in other areas of statistics. In this work, we present two PFNs for B…
stat.ML2026
Just add noise: Debiasing tree-based variable importance in mixed data
Jiahe Li, Omar Melikechi
Variable importance scores from tree-based methods such as random forests favor continuous predictors over categorical ones. We present a theoretical analysis of this bias and prop…
stat.ME2026
Causal Stability Selection
Falco J. Bargagli-Stoffi, Omar Melikechi
Identifying covariates that modify treatment effects is a central problem in causal inference. Yet existing data-adaptive procedures do not provide finite-sample control over the e…